3/1/2022

Why visualize data?

Good visualizations can give:

* Powerful summaries of the underlying data 

* Communicate insights often to audiences who do not have the same
    luxury of spending so much time with the data as you do. 

As a Data analyst/ Scientist, it’s your responsibility to give the necessary high level summaries or takeaways in any data visual you create.

Some Features of Good Visualizations

* Clear on what it's communicating

* Well defined axis, scaling and labels

* Good choice of colors and anotations (visually appealing)

* Less is more

Some Features of Bad Visualizations

* Cluttered,too much going on in the chart with no clear communication goal

* Truncating axes to start at non-zero values which distorts interpretation

* Poor choice of colors

* Unnecessary 3D-fying 

An Example of a Bad Visualization

What’s wrong with this plot?

What’s wrong with that plot?

The visualization is bad because:

* It's vague, putting together all movie ratings does help the
    audience identify what you're trying to communicate.
    
* The rating categories are too many. Remember, good visuals give high 
    level summaries (less is more)
    
* The pie chart used here is not the best tool for comparing multiple 
    categories. 
    
* Pie charts also make it difficult for your audience to judge the relative 
    sizes of the slices.
    
Let's make this visualization better.
    

An Example of a Good Visualization